Instructions to use aalonso-developer/vit-base-clothing-leafs-example-full-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aalonso-developer/vit-base-clothing-leafs-example-full-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aalonso-developer/vit-base-clothing-leafs-example-full-simple") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("aalonso-developer/vit-base-clothing-leafs-example-full-simple") model = AutoModelForImageClassification.from_pretrained("aalonso-developer/vit-base-clothing-leafs-example-full-simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aalonso-developer/vit-base-clothing-leafs-example-full-simple: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example-full-simple/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aalonso-developer/vit-base-clothing-leafs-example-full-simple/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example-full-simple/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 25f7cab66952bc0a28b2a6d5bf845ef04c67e211c09bb57f3ef310bcc3cae399
- Size of remote file:
- 343 MB
- SHA256:
- ffb7d1d5545df75312a8a73417386b08542dde6d870f706c5047c94dcc3f4a97
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